Decision Support
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This study identifies a broader set of objectives, decisions and constraints to be integrated into the next generation operational research models. Including these changes would support evaluation of a suite of response options and the efficient resource packages necessary to achieve response objectives, aiding decision maker’s ability to minimize responder exposure while reducing the social, ecological and economic impacts of wildfires. Researchers follow with a proposed framework for expanding current large fire decision support systems, and conclude by briefly highlighting critical research needs and organizational changes necessary to create and implement these tools and overcome the negative consequences of positive feedbacks derived from historical and current wildfire management policies and strategies.
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This study compared resultant travel rates to LiDAR-derived estimates of slope, vegetation density and ground surface roughness using linear mixed effects modelling to quantify the relationships between these landscape conditions and travel rates. The best-fit model revealed significant negative relationships between travel rates and each of the three landscape conditions, suggesting that, in order of decreasing magnitude, as density, slope and roughness increase, travel rates decrease. Model coefficients were used to map travel impedance within the study area using LiDAR data, which enabled mapping the most efficient routes from fire crew locations to safety zones and provided an estimate of travel time.
Access website and tools.
The After Fire Toolkit and Information website is where managers, landowners, or communities can find guidance for assessing and preventing potential damage due to post-fire flooding and related events. Browse this site to find information on the research, methods, and tools available for measuring and reducing risks associated with post-fire flooding, debris flows and sedimentation.
Read the report.
The goals of the National Forest and Rangeland Management Initiative are to:
- Examine existing forest and rangeland management authorities and programs to determine their strengths and weaknesses;
- Perform a detailed investigation of the role of collaboratives in landscape restoration;
- Create a mechanism for states and land managers to share best practices, case studies and policy options for forest and rangeland management; and
- Recommend improved forest and rangeland management authorities and encourage more effective collaboration.
This report outlines the launch year of the Initiative and includes both administrative and legislative recommendations.
View guide.
The Interagency Fire Unmanned Aircraft Systems Operations Guide standardizes the processes and procedures for interagency use of unmanned aircraft systems (UAS), including pilot inspections and approvals. In support of fire management goals and objectives, the aviation community references these standards to utilize UAS in a safe, effective, and efficient manner. This guide further serves as a risk assessment for fire UAS operations and meets federal requirements for aviation safety and operational planning pertaining to recurring aviation missions. Agency level policy and guidance is provided through established federal or state plans and processes.
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This brief summarizes data and studies to determine whether the results of JFSP-funded projects are reaching potential users and informing management decisions and actions. Those studies have helped identify issues and influence changes within the program. While some studies showed that JFSP-funded research is being used for planning and for supporting treatment prescriptions, they also identified barriers that prevent greater use of fire science information by the broader fire management community. These outcomes studies are an important tool to help the JFSP address those barriers and continue to make program improvements.
Access data portal.
The BLM’s Landscape Approach Data Portal is a one-stop source for geospatial data, maps, models and reports produced by BLM’s landscape initiatives including the: Rapid Ecoregional Assessments (REAs), Fire & Invasives Assessment (FIAT) program, and Sage-Grouse Initiative.
Access catalog.
The USGS Science Data Catalog provides seamless access to USGS research and monitoring data from across the nation. Users have the ability to search, browse, or use a map-based interface to discover data.
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This report provides an updated process for mapping relative habitat suitability and management categories for sage-grouse in Nevada and northeastern California.
Updates include:
- adding radio and GPS telemetry locations from sage-grouse monitored at multiple sites during 2014 to the original location dataset beginning in 1998
- integrating output from high resolution maps (1–2 m2) of sagebrush and pinyon-juniper cover as covariates in resource selection models
- modifying the spatial extent of the analyses to match newly available vegetation layers
- explicit modeling of relative habitat suitability during three seasons (spring, summer, winter) that corresponded to critical life history periods for sage-grouse (breeding, brood-rearing, over-wintering)
- accounting for differences in habitat availability between more mesic sagebrush steppe communities in the northern part of the study area and drier Great Basin sagebrush in more southerly regions by categorizing continuous region-wide surfaces of habitat suitability index (HSI) with independent locations falling within two hydrological zones
- integrating the three seasonal maps into a composite map of annual relative habitat suitability
- deriving updated land management categories based on previously determined cut-points for intersections of habitat suitability and an updated index of sage-grouse abundance and space-use (AUI)
- masking urban footprints and major roadways out of the final map products.
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This study analyzed seasonal variation in the relative availability of soil water for the years 2001, 2004, and 2007, representing respectively, low, moderate, and high rankings of areas burned. For these selected years, the model predicted where forest fires >1 km occurred and did not occur at ~100,000 randomly located pixels with an average accuracy of 69%. The model identified four seasonal combinations, most of which included exhaustion of available water storage capacity during the summer as critical; two combinations involving antecedent conditions the previous spring or fall accounted for 86% of the predicted fires. The approach introduced in this paper can help identify forested areas where management efforts to reduce fire hazards might prove most beneficial.